Document Type
Article
Publication Date
2026
DOI
10.1080/00913367.2026.2735425
Publication Title
Journal of Advertising
Volume
Advance online publication
Pages
1-20
Abstract
Generative artificial intelligence (GenAI)is rapidly reconfiguring advertising from message delivery and optimization to relationship-like exchanges between consumers and brands. While existing work has explained these interactions through social response accounts and interpersonal relationship theories, this lens risks overlooking a defining structural mismatch: AI agents convincingly enact relational characteristics but cannot experience relational benefits, costs, or commitment. Perceived mutuality can be high even when the underlying relational capacity for reciprocity is absent. We introduce human–AI asymmetric relationship theory (HAART), which conceptualizes AI-mediated relationships as relationally expressive yet structurally one-sided. HAART advances three tenets: (1) inherent AI agent characteristics limit relational reciprocity; (2) AI agents mask these limits through performative relationship actions, defined as linguistic, paralinguistic, and interactional behaviors that simulate relational engagement; and (3) when this masking succeeds, an asymmetric relationship emerges, characterized by asymmetries in dependence, risk, and control. We develop six propositions that detail the positive (e.g., enhanced support) and negative (e.g., heightened vulnerability) consequences for consumers and brands, and provide implications for theory, practice, and policy.
Rights
© 2026 The Authors.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ORCID
0000-0001-8832-703X (Thomas)
Original Publication Citation
Thomas, V. L., Shoenberger, H., Gvirtz, A., Sands, S., & Willemsen, L. (2026). Advertising with HAART: Introducing human-AI asymmetric relationship theory. Journal of Advertising. Advance online publication. https://doi.org/10.1080/00913367.2026.2735425
Repository Citation
Thomas, Veronica L.; Shoenberger, Heather; Gvirtz, Andrés; Sands, Sean; and Willemsen, Lotte, "Advertising with HAART: Introducing Human-AI Asymmetric Relationship Theory" (2026). Marketing Faculty Publications. 44.
https://digitalcommons.odu.edu/marketing_pubs/44
Supplemental Material
Included in
Advertising and Promotion Management Commons, Artificial Intelligence and Robotics Commons, Graphics and Human Computer Interfaces Commons, Marketing Commons